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This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5662
  • Accuracy: 0.8065

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5234 1.0 6463 0.5311 0.7852
0.4135 2.0 12926 0.5020 0.8039
0.3246 3.0 19389 0.5662 0.8065

Testing results

    precision    recall  f1-score   support

       0      0.815     0.821     0.818      4449
       1      0.752     0.773     0.762      4071
       2      0.852     0.823     0.837      4245

accuracy                          0.806     12765

macro avg 0.806 0.806 0.806 12765 weighted avg 0.807 0.806 0.807 12765

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.0.0
  • Datasets 2.11.0
  • Tokenizers 0.14.1
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